Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "139"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 139 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 22 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 22 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 139, Node N13:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459998 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.197555 1.342728 1.186868 -0.941130 0.421022 -0.359026 -1.847791 -0.492085 0.6007 0.6017 0.3655 nan nan
2459997 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - nan nan inf inf nan nan nan nan nan nan nan nan nan
2459996 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.895669 1.461300 1.385825 -1.143269 0.669931 -0.757478 -1.227795 0.227342 0.6245 0.6266 0.3767 nan nan
2459995 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.666108 1.532931 1.473621 -1.148881 0.822231 -0.398544 -0.335904 0.703216 0.6036 0.6048 0.3790 nan nan
2459994 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.331711 1.511766 1.416321 -1.067755 0.611539 -0.284747 -0.171244 0.601544 0.5980 0.5963 0.3770 nan nan
2459993 RF_maintenance 100.00% 100.00% 100.00% 0.00% - - 238.758406 237.840226 inf inf 2730.096528 2728.831814 4589.313071 4566.236430 nan nan nan nan nan
2459991 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.511850 1.973235 1.613324 -0.857397 1.225660 -0.345117 -0.670859 -0.115464 0.6196 0.6115 0.3737 nan nan
2459990 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.238969 1.803647 1.637512 -0.722851 1.051709 -0.308176 -0.744491 -0.064354 0.6160 0.6097 0.3704 nan nan
2459989 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.315958 1.855521 1.675523 -0.706278 0.742214 -0.822732 -0.922747 -0.178496 0.6092 0.6054 0.3713 nan nan
2459988 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.538032 2.133065 1.640840 -0.805840 0.923125 -0.431909 -0.004366 0.294476 0.6097 0.6085 0.3657 nan nan
2459987 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.333949 1.417755 1.447912 -1.085154 -0.081421 -0.355512 -1.942236 -1.010282 0.6205 0.6163 0.3631 nan nan
2459986 RF_maintenance 100.00% 0.00% 0.00% 0.00% - - 1.556257 1.814030 1.595988 -1.023002 0.654999 6.808308 0.614950 14.006658 0.6356 0.6341 0.3275 nan nan
2459985 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.534989 1.500301 1.336053 -0.833124 0.238524 -1.167339 -0.619552 0.179973 0.6184 0.6156 0.3718 nan nan
2459984 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.782731 1.551550 1.414890 -0.832248 0.941467 -0.589018 -0.745238 -0.518754 0.6310 0.6323 0.3507 nan nan
2459983 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.114408 -0.176024 1.470231 -0.839423 0.808179 -0.438120 -0.368120 -0.428077 0.6416 0.6611 0.3155 nan nan
2459982 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.677168 0.602346 0.839678 -1.137902 -0.878253 -0.930533 -0.281767 -1.426429 0.6832 0.6873 0.2881 nan nan
2459981 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.822945 0.024241 1.785473 -0.730061 1.195661 -1.083848 -0.365829 0.302942 0.6181 0.6227 0.3703 nan nan
2459980 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.673381 -0.155047 1.287751 -1.154340 0.352244 -1.439508 0.726614 -1.506787 0.6556 0.6636 0.3043 nan nan
2459979 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.726490 -0.141128 1.384920 -1.029709 0.695672 -1.397232 -1.231275 -0.288140 0.6114 0.6191 0.3716 nan nan
2459978 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.777718 -0.074015 1.595547 -0.915646 0.723953 -1.100068 -0.928032 -0.174244 0.6115 0.6186 0.3782 nan nan
2459977 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 1.139508 -0.072078 1.295252 -1.051462 0.629719 -1.384103 -1.145565 0.064470 0.5757 0.5845 0.3385 nan nan
2459976 RF_maintenance 0.00% 0.00% 0.00% 0.00% - - 0.909939 -0.058542 1.467250 -1.012742 0.912279 -1.028725 -0.712418 -0.094504 0.6159 0.6227 0.3715 nan nan

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 139: 2459998

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance nn Shape 1.342728 1.197555 1.342728 1.186868 -0.941130 0.421022 -0.359026 -1.847791 -0.492085

Antenna 139: 2459997

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Shape nan nan nan inf inf nan nan nan nan

Antenna 139: 2459996

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Shape 1.895669 1.895669 1.461300 1.385825 -1.143269 0.669931 -0.757478 -1.227795 0.227342

Antenna 139: 2459995

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Shape 1.666108 1.666108 1.532931 1.473621 -1.148881 0.822231 -0.398544 -0.335904 0.703216

Antenna 139: 2459994

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance nn Shape 1.511766 1.331711 1.511766 1.416321 -1.067755 0.611539 -0.284747 -0.171244 0.601544

Antenna 139: 2459993

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power inf 238.758406 237.840226 inf inf 2730.096528 2728.831814 4589.313071 4566.236430

Antenna 139: 2459991

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance nn Shape 1.973235 1.511850 1.973235 1.613324 -0.857397 1.225660 -0.345117 -0.670859 -0.115464

Antenna 139: 2459990

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance nn Shape 1.803647 1.803647 1.238969 -0.722851 1.637512 -0.308176 1.051709 -0.064354 -0.744491

Antenna 139: 2459989

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance nn Shape 1.855521 1.855521 1.315958 -0.706278 1.675523 -0.822732 0.742214 -0.178496 -0.922747

Antenna 139: 2459988

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance nn Shape 2.133065 2.133065 1.538032 -0.805840 1.640840 -0.431909 0.923125 0.294476 -0.004366

Antenna 139: 2459987

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.447912 1.333949 1.417755 1.447912 -1.085154 -0.081421 -0.355512 -1.942236 -1.010282

Antenna 139: 2459986

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance nn Temporal Discontinuties 14.006658 1.814030 1.556257 -1.023002 1.595988 6.808308 0.654999 14.006658 0.614950

Antenna 139: 2459985

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Shape 1.534989 1.500301 1.534989 -0.833124 1.336053 -1.167339 0.238524 0.179973 -0.619552

Antenna 139: 2459984

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Shape 1.782731 1.782731 1.551550 1.414890 -0.832248 0.941467 -0.589018 -0.745238 -0.518754

Antenna 139: 2459983

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.470231 1.114408 -0.176024 1.470231 -0.839423 0.808179 -0.438120 -0.368120 -0.428077

Antenna 139: 2459982

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 0.839678 0.677168 0.602346 0.839678 -1.137902 -0.878253 -0.930533 -0.281767 -1.426429

Antenna 139: 2459981

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.785473 0.024241 0.822945 -0.730061 1.785473 -1.083848 1.195661 0.302942 -0.365829

Antenna 139: 2459980

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.287751 -0.155047 0.673381 -1.154340 1.287751 -1.439508 0.352244 -1.506787 0.726614

Antenna 139: 2459979

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.384920 0.726490 -0.141128 1.384920 -1.029709 0.695672 -1.397232 -1.231275 -0.288140

Antenna 139: 2459978

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.595547 -0.074015 0.777718 -0.915646 1.595547 -1.100068 0.723953 -0.174244 -0.928032

Antenna 139: 2459977

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.295252 1.139508 -0.072078 1.295252 -1.051462 0.629719 -1.384103 -1.145565 0.064470

Antenna 139: 2459976

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
139 N13 RF_maintenance ee Power 1.467250 -0.058542 0.909939 -1.012742 1.467250 -1.028725 0.912279 -0.094504 -0.712418
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